Kevin William Watts

Bio: Kevin William Watts is an academic researcher from Google. The author has contributed to research in topics: Object (computer science) & Controller (computing). The author has an hindex of 6, co-authored 8 publications receiving 205 citations.

Methods and systems for distributing remote assistance to facilitate robotic object manipulation

Abstract: Methods and systems for distributing remote assistance to facilitate robotic object manipulation are provided herein. Regions of a model of objects in an environment of a robotic manipulator may be determined, where each region corresponds to a different subset of objects with which the robotic manipulator is configured to perform a respective task. Certain tasks may be identified, and a priority queue of requests for remote assistance associated with the identified tasks may be determined based on expected times at which the robotic manipulator will perform the identified tasks. At least one remote assistor device may then be requested, according to the priority queue, to provide remote assistance with the identified tasks. The robotic manipulator may then be caused to perform the identified tasks based on responses to the requesting, received from the at least one remote assistor device, that indicate how to perform the identified tasks.

Associating semantic location data with automated environment mapping

Abstract: Systems and methods are provided for generating maps with semantic labels. A computing device can determine a first map that includes features located at first positions and semantic labels located at semantic positions, and determine a second map that includes at least some of the features located at second positions. The computing device can identify a first region with fixed features located at first positions and corresponding equivalent second positions. The computing device can identify a second region with moved features located at first positions and corresponding non-equivalent second positions. The computing device can determine one or more transformations between first positions and second positions. The computing device can assign the semantic labels to the second map at second semantic positions, where the second semantic positions are the same in the first region, and where the second semantic positions in the second region are based on the transformation(s).

Virtual moving safety limits for vehicles transporting objects

Abstract: Example systems and methods are disclosed for implementing vehicle operation limits to prevent vehicle load failure during vehicle teleoperation. The method may include receiving sensor data from sensors on a vehicle that carries a load. The vehicle may be controlled by a remote control system. The load weight and dimensions may be determined based on the sensor data. In order to prevent a vehicle load failure, a forward velocity limit and an angular velocity limit may be calculated. Vehicle load failures may include the vehicle tipping over, the load tipping over, the load sliding off of the vehicle, or collisions. The vehicle carrying the load may be restricted from exceeding the forward velocity limit and/or the angular velocity limit during vehicle operation. The remote control system may display a user interface indicating to a remote operator the forward velocity limit and the angular velocity limit.

Using laser sensors to augment stereo sensor readings for robotic devices

Abstract: An example system includes one or more laser sensors on a robotic device, where the one or more laser sensors are configured to produce laser sensor data indicative of a first area within a first distance in front of the robotic device. The system further includes one or more stereo sensors on the robotic device, where the stereo sensors on the robotic device are configured to produce stereo sensor data indicative of a second area past a second distance in front of the robotic device. The system also includes a controller configured to receive the laser sensor data, receive the stereo sensor data, detect one or more objects in front of the robotic device based on at least one of the laser sensor data and the stereo sensor data, and provide instructions for the robotic device to navigate based on the one or more detected objects.

Ground plane detection to verify depth sensor status for robot navigation

Abstract: An example method includes determining a target area of a ground plane in an environment of a mobile robotic device, where the target area of the ground plane is in front of the mobile robotic device in a direction of travel of the mobile robotic device. The method further includes receiving depth data from a depth sensor on the mobile robotic device. The method also includes identifying a portion of the depth data representative of the target area. The method additionally includes determining that the portion of the depth data lacks information representing at least one section of the target area. The method further includes providing an output signal identifying at least one zone of non-traversable space for the mobile robotic device in the environment, where the at least one zone of non-traversable space corresponds to the at least one section of the target area.

Handheld dimensioning system with measurement-conformance feedback

Abstract: A system and method for obtaining a dimension measurement that conforms to a conformance criteria is disclosed. The dimensioning system provides either (i) feedback to confirm that the measurement complies with the criteria or (ii) information on how the measurement geometry could be adjusted in order to provide a compliant measurement in a subsequent dimension measurement.

Handheld dimensioner with data-quality indication

Abstract: A handheld dimensioner with a user interface configured to present a quality indicator is disclosed. The handheld dimensioner is configured to capture three-dimensional (3D) data and assess the three-dimensional-data's quality. Based on this quality, a quality indicator may be generated and presented to a user via the user interface. This process may be repeated while the user repositions the handheld dimensioner. In this way, the user may use the quality indicators generated at different positions to find an optimal position for a particular dimension measurement.

Dimensioning system with guided alignment

Abstract: A dimensioning system including a computing device running an alignment software program is disclosed. The alignment software uses range information from a range sensor in order to generate alignment messages. The alignment messages may help a user define a frame of reference and align the dimensioning system's range sensor for improved dimensioning performance.

System and method for dimensioning

Abstract: A system and method for structured-light dimensioning is disclosed. The method includes combining multiple images using different camera settings to provide all of the information necessary dimensioning. What results is an improved ability to sense a light pattern reflected from an object's surfaces, especially when the lighting and/or object color make imaging all surfaces simultaneously difficult.

Handheld dimensioning system with feedback

Abstract: A handheld dimensioning system that analyzes a depth map for null-data pixels to provide feedback is disclosed. Null-data pixels correspond to missing range data and having too many in a depth map may lead to dimensioning errors. Providing feedback based on the number of null-data pixels helps a user understand and adapt to different dimensioning conditions, promotes accuracy, and facilitates handheld applications.